metadata
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_keras_callback
model-index:
- name: kaytoo2022/t5_technical_qa_with_react
results: []
inference: true
library_name: transformers
pipeline_tag: text2text-generation
widget:
- text: |-
summarize: function Example() {
let [isLoading, setIsLoading] = React.useState(false);
let handlePress = () => {
// Trigger button pending state
setIsLoading(true);
setTimeout(() => {
// Cancel button pending state
setIsLoading(false);
}, 3000);
};
return (
<Button variant="primary" isPending={isLoading} onPress={handlePress}>
Click me!
</Button>
);
}
example_title: Question answering
- text: >-
question: What does the setTimeout function do? context: function
Example() {
let [isLoading, setIsLoading] = React.useState(false);
let handlePress = () => {
// Trigger button pending state
setIsLoading(true);
setTimeout(() => {
// Cancel button pending state
setIsLoading(false);
}, 3000);
};
return (
<Button variant="primary" isPending={isLoading} onPress={handlePress}>
Click me!
</Button>
);
}
example_title: Summarization
kaytoo2022/t5_technical_qa_with_react
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 2.0191
- Validation Loss: 2.0546
- Epoch: 3
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
Train Loss | Validation Loss | Epoch |
---|---|---|
2.5717 | 2.2548 | 0 |
2.2680 | 2.1607 | 1 |
2.1248 | 2.1008 | 2 |
2.0191 | 2.0546 | 3 |
Framework versions
- Transformers 4.42.4
- TensorFlow 2.17.0
- Datasets 2.20.0
- Tokenizers 0.19.1